Detroit, Michigan, United States
Open to any quantitative or computational contracts Note: I cannot DM on LinkedIn. If interested in hiring or collaboration, please contact me at the inbox on my website, likelyllc.com Previously worked in scientific computing at SAS as a software developer for ~3 years, and a research statistician at the University of Michigan Department of Cardiovascular Medicine, among many other research positions prior to earning my masters. I've worked on many advanced statistical models, including building Bayesian models to forecast player performance with the Tampa Bay Rays and advanced models for fMRI data analysis in the University of Michigan Department of Psychiatry. I've worked in psychiatry departments, gynecology departments, or computer science departments on statistical modeling or developing software related to modeling. I take pride in developing re-usable solutions to problems on real data. For a better idea about some of the things I do, take a look at my website for some highlights and memoirs: likellc.com calendly.com/andrezapico likelyllc.com github.com/drezap Andre Zapico CEO Likely LLC likelyllc.com Previous Software Developer Scientific Computing The SAS Institute, Inc. ME Information and Communication Engineering University of Electronic Science and Technology of China Thesis: Radar Waveform Design with Artificial Neural Networks Stan Developer mc-stan.org BS Mathematics, 2017 BS Statistics, 2017 The University of Michigan, Ann Arbor University of Michigan, Ann Arbor 2017
- Scientific Computing Engineering - improve the performance of econometrics models and internal research under the direction of the time series engineering team and scientific computing team - Former manager: Sr. Manager, Advanced Analytics, Time Series Engineering, Ji Shen, PhD - Former manager: Head of Econometrics and Time Series Analysis Xilong Chen, PhD, PhD
likelyllc.com Selected Clients: The Tampa Bay Rays University of Michigan, Department of Cardiovascular Medicine
- Department of Cardiovascular Medicine - with Professor of Radiology; Chief of Cardiovascular Medicine, Nuclear Cardiology Venkatesh Murthy MD, PhD
- use hierarchical/multilevel models to determine association of electromechanic morcellator with blood loss during uterine morcellation during hysterectomy - survey data analysis - coordinate research - with Professor Obstetrics and Gynecology Michelle Louie, MD, MSCR, FACOG, MS - R, SAS, brms, rstan
- develop Gaussian process library for the Stan math library in C++ - develop models using Gaussian processes including survival models, time series models, regression models, multinomial outcome models - robust unit testing of developed software - with Professor Computational Bayesian Modeling Aki Vehtari, PhD - with Michael Riis Anderson, PhD - C++, Stan, RStan, CmdStan, PyStan, Linux, LaTex